Ning Xin, Deng Yaoliang
Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Province, People's Republic of China.
Onco Targets Ther. 2017 Mar 20;10:1673-1686. doi: 10.2147/OTT.S131386. eCollection 2017.
Genomic profiling can be used to identify the predictive effect of genomic subsets for determining prognosis in bladder urothelial carcinoma (BUC) after radical cystectomy. This study aimed to investigate potential gene and pathway markers associated with prognosis in BUC.
A microarray dataset of BUC was obtained from The Cancer Genome Atlas database. Differentially expressed genes (DEGs) were identified by DESeq of the R platform. Kaplan-Meier analysis was applied for prognostic markers. Key pathways and genes were identified using bioinformatics tools, such as gene set enrichment analysis, gene ontology, the Kyoto Encyclopedia of Genes and Genomes, gene multiple association network integration algorithm (GeneMANIA), Search Tool for the Retrieval of Interacting Genes/Proteins, and Molecular Complex Detection.
A comparative gene set enrichment analysis of tumor and adjacent normal tissues suggested BUC tumorigenesis resulted mainly from enrichment of cell cycle and DNA damage and repair-related biological processes and pathways, including TP53 and mitotic recombination. Two hundred and fifty-six genes were identified as potential prognosis-related DEGs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that the potential prognosis-related DEGs were enriched in angiogenesis, including the cyclic adenosine monophosphate biosynthetic process, cyclic guanosine monophosphate-protein kinase G, mitogen-activated protein kinase, Rap1, and phosphoinositide-3-kinase-AKT signaling pathway. Nine hub genes, , , , , , , , , and , were identified from the intersection of protein-protein interaction and GeneMANIA networks. Module analysis of protein-protein interaction and GeneMANIA networks mainly showed enrichment of the cyclic guanosine monophosphate-protein kinase G signaling pathway, angiogenesis, cell proliferation, and differentiation, which are associated with tumor angiogenesis and cancer prognosis.
Genes and pathways related to cell cycle and DNA damage and repair may play a crucial role in BUC pathogenesis, whereas those pertaining to tumor angiogenesis may be key factors in influencing BUC prognosis, especially in advanced disease stages.
基因组分析可用于识别基因组亚组对根治性膀胱切除术后膀胱尿路上皮癌（BUC）预后的预测作用。本研究旨在探究与BUC预后相关的潜在基因和信号通路标志物。
从癌症基因组图谱数据库获取BUC的微阵列数据集。通过R平台的DESeq鉴定差异表达基因（DEG）。应用Kaplan-Meier分析评估预后标志物。使用生物信息学工具，如基因集富集分析、基因本体论、京都基因与基因组百科全书、基因多重关联网络整合算法（GeneMANIA）、检索相互作用基因/蛋白质的搜索工具和分子复合物检测，来识别关键信号通路和基因。
肿瘤组织与癌旁正常组织的比较基因集富集分析表明，BUC的肿瘤发生主要源于细胞周期以及DNA损伤与修复相关生物学过程和信号通路的富集，包括TP53和有丝分裂重组。256个基因被鉴定为潜在的预后相关DEG。基因本体论和京都基因与基因组百科全书分析显示，潜在的预后相关DEG在血管生成中富集，包括环磷酸腺苷生物合成过程、环磷酸鸟苷 - 蛋白激酶G、丝裂原活化蛋白激酶Rap1和磷脂酰肌醇 - 3 - 激酶 - AKT信号通路。从蛋白质 - 蛋白质相互作用和GeneMANIA网络的交集处鉴定出9个枢纽基因，分别为[此处未给出具体基因名称]。蛋白质 - 蛋白质相互作用和GeneMANIA网络的模块分析主要显示环磷酸鸟苷 - 蛋白激酶G信号通路、血管生成、细胞增殖和分化的富集，这些与肿瘤血管生成和癌症预后相关。
与细胞周期以及DNA损伤与修复相关的基因和信号通路可能在BUC发病机制中起关键作用，而与肿瘤血管生成相关的基因和信号通路可能是影响BUC预后的关键因素，尤其是在疾病晚期。
